Mapping hippocampal and thalamic atrophy in epilepsy: A 7-T magnetic resonance imaging study.

OBJECTIVE: Epilepsy patients are often grouped together by clinical variables. Quantitative neuroimaging metrics can provide a data-driven alternative for grouping of patients. In this work, we leverage ultra-high-field 7-T structural magnetic resonance imaging (MRI) to characterize volumetric atrophy patterns across hippocampal subfields and thalamic nuclei in drug-resistant focal epilepsy. METHODS: Forty-two drug-resistant epilepsy patients and 13 controls with 7-T structural neuroimaging were included in this study. We measured hippocampal subfield and thalamic nuclei volumetry, and applied an unsupervised machine learning algorithm, Latent Dirichlet Allocation (LDA), to estimate atrophy patterns across the hippocampal subfields and thalamic nuclei of patients. We studied the association between predefined clinical groups and the estimated atrophy patterns. Additionally, we used hierarchical clustering on the LDA factors to group patients in a data-driven approach. RESULTS: In patients with mesial temporal sclerosis (MTS), we found a significant decrease in volume across all ipsilateral hippocampal subfields (false discovery rate-corrected p [pFDR] < .01) as well as in some ipsilateral (pFDR < .05) and contralateral (pFDR < .01) thalamic nuclei. In left temporal lobe epilepsy (L-TLE) we saw ipsilateral hippocampal and some bilateral thalamic atrophy (pFDR < .05), whereas in right temporal lobe epilepsy (R-TLE) extensive bilateral hippocampal and thalamic atrophy was observed (pFDR < .05). Atrophy factors demonstrated that our MTS cohort had two atrophy phenotypes: one that affected the ipsilateral hippocampus and one that affected the ipsilateral hippocampus and bilateral anterior thalamus. Atrophy factors demonstrated posterior thalamic atrophy in R-TLE, whereas an anterior thalamic atrophy pattern was more common in L-TLE. Finally, hierarchical clustering of atrophy patterns recapitulated clusters with homogeneous clinical properties. SIGNIFICANCE: Leveraging 7-T MRI, we demonstrate widespread hippocampal and thalamic atrophy in epilepsy. Through unsupervised machine learning, we demonstrate patterns of volumetric atrophy that vary depending on disease subtype. Incorporating these atrophy patterns into clinical practice could help better stratify patients to surgical treatments and specific device implantation strategies.

iEEG-recon: A fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices.

OBJECTIVE: Clinicians use intracranial electroencephalography (iEEG) in conjunction with noninvasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms. METHODS: We created iEEG-recon, a scalable electrode reconstruction pipeline for semiautomatic iEEG annotation, rapid image registration, and electrode assignment on brain magnetic resonance imaging (MRI). Its modular architecture includes a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts. RESULTS: We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography and stereoelectroencephalography cases with a 30-min running time per case (including semiautomatic electrode labeling and reconstruction). iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and postimplant T1-MRI visual inspections. We also found that our use of ANTsPyNet deep learning-based brain segmentation for electrode classification was consistent with the widely used FreeSurfer segmentations. SIGNIFICANCE: iEEG-recon is a robust pipeline for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting fast data analysis and integration into clinical workflows. iEEG-recon's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide.

Mapping hippocampal glutamate in mesial temporal lobe epilepsy with glutamate weighted CEST (GluCEST) imaging.

Temporal lobe epilepsy (TLE) is one of the most common subtypes of focal epilepsy, with mesial temporal sclerosis (MTS) being a common radiological and histopathological finding. Accurate identification of MTS during presurgical evaluation confers an increased chance of good surgical outcome. Here we propose the use of glutamate-weighted chemical exchange saturation transfer (GluCEST) magnetic resonance imaging (MRI) at 7 Tesla for mapping hippocampal glutamate distribution in epilepsy, allowing to differentiate lesional from non-lesional mesial TLE. We demonstrate that a directional asymmetry index, which quantifies the relative difference between GluCEST contrast in hippocampi ipsilateral and contralateral to the seizure onset zone, can differentiate between sclerotic and non-sclerotic hippocampi, even in instances where traditional presurgical MRI assessments did not provide evidence of sclerosis. Overall, our results suggest that hippocampal glutamate mapping through GluCEST imaging is a valuable addition to the presurgical epilepsy evaluation toolbox.

Low-field MRI: A report on the 2022 ISMRM workshop.

In March 2022, the first ISMRM Workshop on Low-Field MRI was held virtually. The goals of this workshop were to discuss recent low field MRI technology including hardware and software developments, novel methodology, new contrast mechanisms, as well as the clinical translation and dissemination of these systems. The virtual Workshop was attended by 368 registrants from 24 countries, and included 34 invited talks, 100 abstract presentations, 2 panel discussions, and 2 live scanner demonstrations. Here, we report on the scientific content of the Workshop and identify the key themes that emerged. The subject matter of the Workshop reflected the ongoing developments of low-field MRI as an accessible imaging modality that may expand the usage of MRI through cost reduction, portability, and ease of installation. Many talks in this Workshop addressed the use of computational power, efficient acquisitions, and contemporary hardware to overcome the SNR limitations associated with low field strength. Participants discussed the selection of appropriate clinical applications that leverage the unique capabilities of low-field MRI within traditional radiology practices, other point-of-care settings, and the broader community. The notion of "image quality" versus "information content" was also discussed, as images from low-field portable systems that are purpose-built for clinical decision-making may not replicate the current standard of clinical imaging. Speakers also described technical challenges and infrastructure challenges related to portability and widespread dissemination, and speculated about future directions for the field to improve the technology and establish clinical value.

MRI scarcity in low- and middle-income countries.

Since the introduction of MRI as a sustainable diagnostic modality, global accessibility to its services has revealed a wide discrepancy between populations-leaving most of the population in LMICs without access to this important imaging modality. Several factors lead to the scarcity of MRI in LMICs; for example, inadequate infrastructure and the absence of a dedicated workforce are key factors in the scarcity observed. RAD-AID has contributed to the advancement of radiology globally by collaborating with our partners to make radiology more accessible for medically underserved communities. However, progress is slow and further investment is needed to ensure improved global access to MRI.

Low-field MRI: Clinical promise and challenges.

Modern MRI scanners have trended toward higher field strengths to maximize signal and resolution while minimizing scan time. However, high-field devices remain expensive to install and operate, making them scarce outside of high-income countries and major population centers. Low-field strength scanners have drawn renewed academic, industry, and philanthropic interest due to advantages that could dramatically increase imaging access, including lower cost and portability. Nevertheless, low-field MRI still faces inherent limitations in image quality that come with decreased signal. In this article, we review advantages and disadvantages of low-field MRI scanners, describe hardware and software innovations that accentuate advantages and mitigate disadvantages, and consider clinical applications for a new generation of low-field devices. In our review, we explore how these devices are being or could be used for high acuity brain imaging, outpatient neuroimaging, MRI-guided procedures, pediatric imaging, and musculoskeletal imaging. Challenges for their successful clinical translation include selecting and validating appropriate use cases, integrating with standards of care in high resource settings, expanding options with actionable information in low resource settings, and facilitating health care providers and clinical practice in new ways. By embracing both the promise and challenges of low-field MRI, clinicians and researchers have an opportunity to transform medical care for patients around the world. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.

Home Aerobic Training for Cerebellar Degenerative Diseases: a Randomized Controlled Trial.

Balance training has shown some benefits in cerebellar ataxia whereas the effects of aerobic training are relatively unknown. To determine whether a phase III trial comparing home aerobic to balance training in ambulatory patients with cerebellar ataxia is warranted, we conducted a single-center, assessor-blinded, randomized controlled trial. Nineteen subjects were randomized to aerobic training and 17 subjects to balance training. The primary outcome was improvement in ataxia as measured by the Scale for the Assessment and Rating of Ataxia (SARA). Secondary outcomes included safety, training adherence, and balance improvements. There were no differences between groups at baseline. Thirty-one participants completed the trial, and there were no training-related serious adverse events. Compliance to training was over 70%. There was a mean improvement in ataxia symptoms of 1.9 SARA points (SD 1.62) in the aerobic group compared to an improvement of 0.6 points (SD 1.34) in the balance group. Although two measures of balance were equivocal between groups, one measure of balance showed greater improvement with balance training compared to aerobic training. In conclusion, this 6-month trial comparing home aerobic versus balance training in cerebellar ataxia had excellent retention and adherence to training. There were no serious adverse events, and training was not interrupted by minor adverse events like falls or back pain. There was a significant improvement in ataxia symptoms with home aerobic training compared to balance training, and a phase III trial is warranted. Clinical trial registration number: NCT03701776 on October 8, 2018.

Resting state functional connectivity demonstrates increased segregation in bilateral temporal lobe epilepsy.

OBJECTIVE: Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe seizures. The purpose of this study was to leverage network neuroscience to better understand the interictal whole brain network of bilateral TLE (BiTLE). METHODS: In this study, using a multicenter resting state functional magnetic resonance imaging (rs-fMRI) data set, we constructed whole-brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting-state, whole-brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities. Curves of network density vs each network metric were compared between groups. Finally, we derived a combined metric, which we term the "integration-segregation axis," by combining whole-brain average clustering coefficient and global efficiency curves, and applying principal component analysis (PCA)-based dimensionality reduction. RESULTS: Compared to UTLE, BiTLE had decreased global efficiency (p = .031), and decreased whole brain average participation coefficient across a range of network densities (p = .019). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p = .020). Differences in network properties separate BiTLE and UTLE along the integration-segregation axis, with regions within the axis having a specificity of up to 0.87 for BiTLE. Along the integration-segregation axis, UTLE patients with poor surgical outcomes were distributed in the same regions as BiTLE, and network metrics confirmed similar patterns of increased segregation in both BiTLE and poor outcome UTLE. SIGNIFICANCE: Increased interictal whole-brain network segregation, as measured by rs-fMRI, is specific to BiTLE, as well as poor surgical outcome UTLE, and may assist in non-invasively identifying this patient population prior to intracranial electroencephalography or device implantation.

Quantifying trial-by-trial variability during cortico-cortical evoked potential mapping of epileptogenic tissue.

OBJECTIVE: Measuring cortico-cortical evoked potentials (CCEPs) is a promising tool for mapping epileptic networks, but it is not known how variability in brain state and stimulation technique might impact the use of CCEPs for epilepsy localization. We test the hypotheses that (1) CCEPs demonstrate systematic variability across trials and (2) CCEP amplitudes depend on the timing of stimulation with respect to endogenous, low-frequency oscillations. METHODS: We studied 11 patients who underwent CCEP mapping after stereo-electroencephalography electrode implantation for surgical evaluation of drug-resistant epilepsy. Evoked potentials were measured from all electrodes after each pulse of a 30 s, 1 Hz bipolar stimulation train. We quantified monotonic trends, phase dependence, and standard deviation (SD) of N1 (15-50 ms post-stimulation) and N2 (50-300 ms post-stimulation) amplitudes across the 30 stimulation trials for each patient. We used linear regression to quantify the relationship between measures of CCEP variability and the clinical seizure-onset zone (SOZ) or interictal spike rates. RESULTS: We found that N1 and N2 waveforms exhibited both positive and negative monotonic trends in amplitude across trials. SOZ electrodes and electrodes with high interictal spike rates had lower N1 and N2 amplitudes with higher SD across trials. Monotonic trends of N1 and N2 amplitude were more positive when stimulating from an area with higher interictal spike rate. We also found intermittent synchronization of trial-level N1 amplitude with low-frequency phase in the hippocampus, which did not localize the SOZ. SIGNIFICANCE: These findings suggest that standard approaches for CCEP mapping, which involve computing a trial-averaged response over a .2-1 Hz stimulation train, may be masking inter-trial variability that localizes to epileptogenic tissue. We also found that CCEP N1 amplitudes synchronize with ongoing low-frequency oscillations in the hippocampus. Further targeted experiments are needed to determine whether phase-locked stimulation could have a role in localizing epileptogenic tissue.

Normative intracranial EEG maps epileptogenic tissues in focal epilepsy.

Planning surgery for patients with medically refractory epilepsy often requires recording seizures using intracranial EEG. Quantitative measures derived from interictal intracranial EEG yield potentially appealing biomarkers to guide these surgical procedures; however, their utility is limited by the sparsity of electrode implantation as well as the normal confounds of spatiotemporally varying neural activity and connectivity. We propose that comparing intracranial EEG recordings to a normative atlas of intracranial EEG activity and connectivity can reliably map abnormal regions, identify targets for invasive treatment and increase our understanding of human epilepsy. Merging data from the Penn Epilepsy Center and a public database from the Montreal Neurological Institute, we aggregated interictal intracranial EEG retrospectively across 166 subjects comprising >5000 channels. For each channel, we calculated the normalized spectral power and coherence in each canonical frequency band. We constructed an intracranial EEG atlas by mapping the distribution of each feature across the brain and tested the atlas against data from novel patients by generating a z-score for each channel. We demonstrate that for seizure onset zones within the mesial temporal lobe, measures of connectivity abnormality provide greater distinguishing value than univariate measures of abnormal neural activity. We also find that patients with a longer diagnosis of epilepsy have greater abnormalities in connectivity. By integrating measures of both single-channel activity and inter-regional functional connectivity, we find a better accuracy in predicting the seizure onset zones versus normal brain (area under the curve = 0.77) compared with either group of features alone. We propose that aggregating normative intracranial EEG data across epilepsy centres into a normative atlas provides a rigorous, quantitative method to map epileptic networks and guide invasive therapy. We publicly share our data, infrastructure and methods, and propose an international framework for leveraging big data in surgical planning for refractory epilepsy.

Physical Activity and Fitness Levels of Individuals With Ataxia: A Cross-Sectional Study.

OBJECTIVE: To investigate physical activity levels of individuals with ataxia and correlate fitness to ataxia severity. DESIGN: An observational study SETTING: An outpatient ataxia clinic in a large, tertiary, urban hospital in the US. PARTICIPANTS: Individuals with cerebellar ataxia (N=42). INTERVENTION: Not applicable. MAIN OUTCOME MEASURE: Participants were classified as sedentary or physically active using the International Physical Activity Questionnaire-Short Form (IPAQ-SF). Maximal oxygen consumption (V̇o2max) as an indicator of fitness level was measured, and ataxia severity was determined by the Scale for the Assessment and Rating of Ataxia (SARA). Mixed effect models were used to correlate ataxia severity to fitness levels. RESULTS: Most participants (28 out of 42) lived sedentary lifestyles, and these individuals had poor fitness levels (only 67.3% of their predicted measure). The main barriers to physical activity included lack of energy, lack of time, and fear of falling. There were no differences in age, sex, disease type, disease duration, ataxia severity, fatigue level, and medication use between sedentary and active groups. Measures of V̇o2max, maximal work, maximal heart rate, and anerobic threshold demonstrated statistically significant differences between groups whereas maximal respiratory rate and expired ventilation/carbon dioxide production were similar between groups. When adjusting for age, sex, functional mobility status, and disease duration, ataxia severity was inversely correlated with fitness level in the sedentary group. There was no relationship between ataxia severity and fitness level in the 14 individuals who were physically active. CONCLUSIONS: Lower fitness levels were associated with more ataxia symptoms in the sedentary group. This relationship was not seen in individuals who were more active. Given the poor health outcomes associated with low fitness, physical activity should be encouraged in this population.

Medical Cannabis for Chronic Nonmalignant Pain Management.

PURPOSE OF REVIEW: Cannabis has been used since ancient times for medical and recreational research. This review article will document the validity of how medical cannabis can be utilized for chronic nonmalignant pain management. RECENT FINDINGS: Current cannabis research has shown that medical cannabis is indicated for symptom management for many conditions not limited to cancer, chronic pain, headaches, migraines, and psychological disorders (anxiety and post-traumatic stress disorder). Δ9-Tetrahydrocannabinol (THC) and cannabidiol (CBD) are active ingredients in cannabis that modulate a patient's symptoms. These compounds work to decrease nociception and symptom frequency via the endocannabinoid system. Research regarding pain management is limited within the USA as the Drug Enforcement Agency (DEA) classifies it as a schedule one drug. Few studies have found a limited relationship between chronic pain and medical cannabis use. A total of 77 articles were selected after a thorough screening process using PubMed and Google Scholar. This paper demonstrates that medical cannabis use provides adequate pain management. Patients suffering from chronic nonmalignant pain may benefit from medical cannabis due to its convenience and efficacy.

Which Road to Recovery?: Factors Influencing Postacute Stroke Discharge Destinations: A Delphi Study.

BACKGROUND AND PURPOSE: The criteria for determining the level of postacute care for patients with stroke are variable and inconsistent. The purpose of this study was to identify key factors influencing the selection of postacute level of care for these patients. METHODS: We used a collaborative 4-round Delphi process to achieve a refined list of factors influencing postacute level of care selection. Our Delphi panel of experts consisted of 32 panelists including physicians, physical therapists, occupational therapists, speech-language pathologists, nurses, stroke survivors, administrators, policy experts, and individuals associated with third-party insurance companies. RESULTS: In round 1, 207 factors were proposed, with subsequent discussion resulting in consolidation into 15 factors for consideration. In round 2, 15 factors were ranked with consensus on 10 factors; in round 3,10 factors were ranked with consensus on 9 factors. In round 4, the final round, 9 factors were rated with Likert scores ranging from 5 (most important) to 1(not important). The percentage of panelists who provided a rating of 4 or above were as follows: likelihood to benefit from an active rehabilitation program (97%), need for clinicians with specialized rehabilitation skills (94%), need for active and ongoing medical management and monitoring (84%), ability to tolerate an active rehabilitation program (74%), need for caregiver training to return to the community (48%), family/caregiver support (39%), likelihood to return to community/home (39%), ability to return to physical home environment (32%), and premorbid dementia (16%). CONCLUSIONS: This study provides an expert, consensus-based set of key factors to be considered when determining where stroke patients are discharged for postacute care. These factors may be useful in developing a decision support tool for use in clinical settings.

A framework For brain atlases: Lessons from seizure dynamics.

Brain maps, or atlases, are essential tools for studying brain function and organization. The abundance of available atlases used across the neuroscience literature, however, creates an implicit challenge that may alter the hypotheses and predictions we make about neurological function and pathophysiology. Here, we demonstrate how parcellation scale, shape, anatomical coverage, and other atlas features may impact our prediction of the brain's function from its underlying structure. We show how network topology, structure-function correlation (SFC), and the power to test specific hypotheses about epilepsy pathophysiology may change as a result of atlas choice and atlas features. Through the lens of our disease system, we propose a general framework and algorithm for atlas selection. This framework aims to maximize the descriptive, explanatory, and predictive validity of an atlas. Broadly, our framework strives to provide empirical guidance to neuroscience research utilizing the various atlases published over the last century.

A Tale of Progressive Painless Vision Loss in a 64-Year-Old Man Due to Leber Hereditary Optic Neuropathy.

ABSTRACT: A 64-year-old man presented with painless sequential bilateral vision loss, consistent with optic neuropathy, over the span of months. The significant decline in his visual function was out of proportion to the appearance of the optic nerves (which were not pale) or changes in his retinal nerve fiber layer thickness on optical coherence tomography. Neuroimaging revealed only mild T2 signal abnormality and faint enhancement in the left optic nerve. Extensive workup for potential infectious, metabolic, inflammatory, and ischemic etiologies was unremarkable. Empiric treatment with intravenous steroids did not slow or ameliorate the vision loss. Ultimately, genetic analysis revealed a missense m.11778G>A mutation in mitochondrial MT-ND4 gene, consistent with Leber hereditary optic neuropathy. Initiation of multivitamin supplements and idebenone unfortunately did not result in recovery of vision.

Utility of the AM-PAC "6 Clicks" Basic Mobility and Daily Activity Short Forms to Determine Discharge Destination in an Acute Stroke Population.

IMPORTANCE: The American Heart Association and American Stroke Association recommend early identification of level of rehabilitative care as a priority after stroke. OBJECTIVE: To evaluate the utility of the Activity Measure for Post-Acute Care (AM-PAC) "6 Clicks" Daily Activity and Basic Mobility forms to determine the next level of rehabilitation after hospitalization for adults with stroke. DESIGN: Retrospective cohort design using medical records from 2015 to 2016. SETTING: Major urban hospital. PARTICIPANTS: Patients admitted to the stroke service, with a confirmed stroke, who were seen by a physical or occupational therapist; who had a 6 Clicks Basic Mobility or Daily Activity score at initial evaluation; and who were discharged to home, an acute inpatient rehabilitation facility (IRF), or a subacute skilled nursing facility (SNF). OUTCOMES AND MEASURES: Length of stay and discharge destination. RESULTS: Seven hundred four participants (M age = 68.28 yr; 51.21% female) were included. Analysis of variance and receiver operating characteristic curves were performed. Daily Activity scores were highest for home discharge, lower for IRF discharge, and lowest for SNF discharge; Basic Mobility showed a similar pattern. Cutoff values distinguishing home from further inpatient rehabilitation were 44.50 for Basic Mobility and 39.40 for Daily Activity scores (area under the curve [AUC] = .82 for both forms), with scores of 34.59 (AUC = 0.64) and 31.32 (AUC = 0.67) separating IRF from SNF, respectively. CONCLUSIONS AND RELEVANCE: Therapists should incorporate 6 Clicks scores into their discharge planning. What This Article Adds: This research demonstrates the utility of an outcome measure in the acute care setting that assists in planning discharge destination for patients with stroke.

Comprehensive Stroke Care and Outcomes: Time for a Paradigm Shift.

Worldwide, stroke is prevalent, costly, and disabling in >80 million survivors. The burden of stroke is increasing despite incredible progress and advancements in evidence-based acute care therapies and despite the substantial changes being made in acute care stroke systems, processes, and quality metrics. Although there has been increased global emphasis on the importance of postacute stroke care, stroke system changes have not expanded to include postacute care and outcome follow-up. Our objectives are to describe the gaps and challenges in postacute stroke care and suboptimal stroke outcomes; to report on stroke survivors' and caregivers' perceptions of current postacute stroke care and their call for improvements in follow-up services for recovery and secondary prevention; and, ultimately, to make the case that a paradigm shift is needed in the definition of comprehensive stroke care and the designation of Comprehensive Stroke Center. Three recommendations are made for a paradigm shift in comprehensive stroke care: (1) criteria should be established for designation of rehabilitation readiness for Comprehensive Stroke Centers, (2) The American Heart Association/American Stroke Association implement an expanded Get With The Guidelines-Stroke program and criteria for comprehensive stroke centers to be inclusive of rehabilitation readiness and measure outcomes at 90 days, and (3) a public health campaign should be launched to offer hopeful and actionable messaging for secondary prevention and recovery of function and health. Now is the time to honor the patients' and caregivers' strongest ask: better access and improved secondary prevention, stroke rehabilitation, and personalized care.

Clinical Performance Measures for Stroke Rehabilitation: Performance Measures From the American Heart Association/American Stroke Association.

The American Heart Association/American Stroke Association released the adult stroke rehabilitation and recovery guidelines in 2016. A working group of stroke rehabilitation experts reviewed these guidelines and identified a subset of recommendations that were deemed suitable for creating performance measures. These 13 performance measures are reported here and contain inclusion and exclusion criteria to allow calculation of rates of compliance in a variety of settings ranging from acute hospital care to postacute care and care in the home and outpatient setting.

Grid-like hexadirectional modulation of human entorhinal theta oscillations.

The entorhinal cortex contains a network of grid cells that play a fundamental part in the brain's spatial system, supporting tasks such as path integration and spatial memory. In rodents, grid cells are thought to rely on network theta oscillations, but such signals are not evident in all species, challenging our understanding of the physiological basis of the grid network. We analyzed intracranial recordings from neurosurgical patients during virtual navigation to identify oscillatory characteristics of the human entorhinal grid network. The power of entorhinal theta oscillations showed six-fold modulation according to the virtual heading during navigation, which is a hypothesized signature of grid representations. Furthermore, modulation strength correlated with spatial memory performance. These results demonstrate the connection between theta oscillations and the human entorhinal grid network and show that features of grid-like neuronal representations can be identified from population electrophysiological recordings.

Characterizing the role of the structural connectome in seizure dynamics.

How does the human brain's structural scaffold give rise to its intricate functional dynamics? This is a central question in translational neuroscience that is particularly relevant to epilepsy, a disorder affecting over 50 million subjects worldwide. Treatment for medication-resistant focal epilepsy is often structural-through surgery or laser ablation-but structural targets, particularly in patients without clear lesions, are largely based on functional mapping via intracranial EEG. Unfortunately, the relationship between structural and functional connectivity in the seizing brain is poorly understood. In this study, we quantify structure-function coupling, specifically between white matter connections and intracranial EEG, across pre-ictal and ictal periods in 45 seizures from nine patients with unilateral drug-resistant focal epilepsy. We use high angular resolution diffusion imaging (HARDI) tractography to construct structural connectivity networks and correlate these networks with time-varying broadband and frequency-specific functional networks derived from coregistered intracranial EEG. Across all frequency bands, we find significant increases in structure-function coupling from pre-ictal to ictal periods. We demonstrate that short-range structural connections are primarily responsible for this increase in coupling. Finally, we find that spatiotemporal patterns of structure-function coupling are highly stereotyped for each patient. These results suggest that seizures harness the underlying structural connectome as they propagate. Mapping the relationship between structural and functional connectivity in epilepsy may inform new therapies to halt seizure spread, and pave the way for targeted patient-specific interventions.